Dual View on Clear-Sky Top-of-Atmosphere Albedos from Meteosat Second Generation Satellites
Abstract
:1. Introduction
2. Dual-View Comparison Method
- For each day at that timeslot, we first derive the instantaneous clear-sky TOA albedo image after applying the appropriate masks—e.g., keeping only those pixels for which the cloud-cover layer is zero (as discussed in the following, we are going to apply a number of extra conditions);
- Then, similarly to what is done for monthly hourly products [19,20,21], we use all these images to calculate the monthly “representative albedo image” at that timeslot: in this work, we considered both the mean and the median, and unless otherwise stated we will show results obtained using the median albedo (robust statistics);
- In a common latitude–longitude grid, we can then calculate the grid-box difference for that specific timeslot; in other words, each pixel location x will store the albedo difference
3. One Month: Sample Results and Improvements
3.1. Raw GL-SEV Products
3.2. Masks
3.3. Diurnal-Asymmetry Artefact
3.4. Merged Overhead Albedo
3.5. Visualising the Diurnal-Asymmetry Artefact from the Viewpoint of Each Satellite
4. One Year
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
ADM | Angular Distribution Model |
CERES | Clouds and the Earth’s Radiant Energy System |
CM SAF | Satellite Application Facility on Climate Monitoring |
ERB | Earth’s Radiation Budget |
ESA | European Space Agency |
EUMETSAT | European Organisation for the Exploitation of Meteorological Satellites |
GCOS | Global Climate Observing System |
GEO | Geostationary Orbit |
GERB | Geostationary Earth Radiation Budget |
GL-SEV | SEVIRI ‘GERB-like’ synthetic product |
HDF | Hierarchical Data Format |
LEO | Low Earth Orbit |
MMDC | Monthly Mean Diurnal Cycle |
MSG | Meteosat Second Generation |
NASA | National Aeronautics and Space Administration |
RMSD | (Albedo) Root-Mean Squared Difference |
SEVIRI | Spinning Enhanced Visible and InfraRed Imager |
SYN1deg | Synoptic 1° |
TOA | Top of Atmosphere |
TRMM | Tropical Rainfall Measuring Mission |
UTC | Coordinated Universal Time |
Appendix A
Appendix B
References and Notes
- Bojinski, S.; Verstraete, M.; Peterson, T.C.; Richter, C.; Simmons, A.; Zemp, M. The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy. Bull. Am. Meteorol. Soc. 2014, 95, 1431–1443. [Google Scholar] [CrossRef]
- Pachauri, R.; Allen, M.; Barros, V.; Broome, J.; Cramer, W.; Christ, R.; Church, J.; Clarke, L.; Dahe, Q.; Dasqupta, P.; et al. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; IPCC: Geneva, Switzerland, 2014; p. 151. Available online: https://www.ipcc.ch/report/ar5/syr/ (accessed on 22 April 2021).
- Note that wide-field-of-view instruments, which cannot provide spatial information, are not considered in this work.
- Green, R.N.; Avis, L.M. Validation of ERBS Scanner Radiances. J. Atmos. Ocean. Technol. 1996, 13, 851–862. [Google Scholar] [CrossRef] [Green Version]
- Suttles, J.T.; Wielicki, B.A.; Vemury, S. Top-of-Atmosphere Radiative Fluxes: Validation of ERBE Scanner Inversion Algorithm Using Nimbus-7 ERB Data. J. Appl. Meteorol. 1992, 31, 784–796. [Google Scholar] [CrossRef]
- Loeb, N.G.; Manalo-Smith, N.; Kato, S.; Miller, W.F.; Gupta, S.K.; Minnis, P.; Wielicki, B.A. Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth’s Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite. Part I: Methodology. J. Appl. Meteorol. 2003, 42, 240–265. [Google Scholar] [CrossRef]
- Suttles, J.T.; Green, R.N.; Minnis, P.; Smith, G.L.; Staylor, W.F.; Wielicki, B.A.; Walker, I.J.; Young, D.F.; Taylor, V.R.; Stowe, L.L. Angular Radiation Models for Earth–Atmosphere System, Volume 1—Shortwave Radiation; Technical Report, NASA Report RP–1184; NASA: Washington, DC, USA, 1988.
- Dewitte, S.; Nevens, S. The total solar irradiance climate data record. Astrophys. J. 2016, 830, 25. [Google Scholar] [CrossRef]
- Bretagnon, P.; Francou, G. Planetary Theories in rectangular and spherical variables: VSOP87 solutions. Astron. Astrophys. 1988, 202, 309. [Google Scholar]
- Yang, G.Y.; Slingo, J. The diurnal cycle in the tropics. Mon. Weather. Rev. 2001, 129, 784–801. [Google Scholar] [CrossRef]
- Wielicki, B.A.; Barkstrom, B.R.; Harrison, E.F.; Lee, R.B., III; Smith, G.L.; Cooper, J.E. Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System Experiment. Bull. Am. Meteorol. Soc. 1996, 77, 853–868. [Google Scholar] [CrossRef] [Green Version]
- Schmetz, J.; Pili, P.; Tjemkes, S.; Just, D.; Kerkmann, J.; Rota, S.; Ratier, A. An Introduction to Meteosat Second Generation (MSG). Bull. Am. Meteorol. Soc. 2002, 83, 977–992. [Google Scholar] [CrossRef]
- Harries, J.E.; Russell, J.E.; Hanafin, J.A.; Brindley, H.; Futyan, J.; Rufus, J.; Kellock, S.; Matthews, G.; Wrigley, R.; Last, A.; et al. The Geostationary Earth Radiation Budget Project. Bull. Am. Meteorol. Soc. 2005, 86, 945–960. [Google Scholar] [CrossRef] [Green Version]
- Ratier, A. EUMETSAT Programmes and Future Plans, September 2020. EUM/DG/VWG/20/1191556 v2. Available online: https://www.nesdis.noaa.gov/content/2020-community-meetings-presentations (accessed on 22 April 2021).
- Dewitte, S.; Gonzalez, L.; Clerbaux, N.; Ipe, A.; Bertrand, C.; de Paepe, B. The Geostationary Earth Radiation Budget Edition 1 data processing algorithms. Adv. Space Res. 2008, 41, 1906–1913. [Google Scholar] [CrossRef]
- We Use What Are, at the Time of Writing, the Very Latest Available Products Covering the Dual-View Period: GL-SEV HR V003. Available online: https://gerb.oma.be (accessed on 22 April 2021).
- Clerbaux, N.; Dewitte, S.; Bertrand, C.; Caprion, D.; De Paepe, B.; Gonzalez, L.; Ipe, A.; Russell, J.E.; Brindley, H. Unfiltering of the Geostationary Earth Radiation Budget (GERB) Data. Part I: Shortwave Radiation. J. Atmos. Ocean. Technol. 2008, 25, 1087–1105. [Google Scholar] [CrossRef]
- Su, W.; Corbett, J.; Eitzen, Z.; Liang, L. Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: Methodology. Atmos. Meas. Tech. 2015, 8, 611–632. [Google Scholar] [CrossRef] [Green Version]
- Doelling, D.R.; Sun, M.; Nguyen, L.T.; Nordeen, M.L.; Haney, C.O.; Keyes, D.F.; Mlynczak, P.E. Advances in Geostationary-Derived Longwave Fluxes for the CERES Synoptic (SYN1deg) Product. J. Atmos. Ocean. Technol. 2016, 33, 503–521. [Google Scholar] [CrossRef]
- Urbain, M.; Clerbaux, N.; Ipe, A.; Tornow, F.; Hollmann, R.; Baudrez, E.; Velazquez Blazquez, A.; Moreels, J. The CM SAF TOA Radiation Data Record Using MVIRI and SEVIRI. Remote Sens. 2017, 9, 466. [Google Scholar] [CrossRef] [Green Version]
- Clerbaux, N.; Urbain, M.; Ipe, A.; Baudrez, E.; Velazquez-Blazquez, A.; Akkermans, T.; Hollmann, R.; Fuchs, P.; Selbach, N.; Werscheck, M. CMSAF TOARadiationGERB/SEVIRIData Record-Edition 2. 2017. Available online: https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=TOA_GERB_V002 (accessed on 22 April 2021).
- Bertrand, C.; Clerbaux, N.; Ipe, A.; Dewitte, S.; Gonzalez, L. Angular distribution models anisotropic correction factors and sun glint: A sensitivity study. Int. J. Remote Sens. 2006, 27, 1741–1757. [Google Scholar] [CrossRef]
- The albedo is set to 1 where it exceeds this value. Such pixels are not masked, to help identify and address potential issues.
- Russell, J. Quality Summary: GERB L2 Edition 1 Products; Technical Report; 2017; Available online: http://cedadocs.ceda.ac.uk/1358/ (accessed on 22 April 2021).
- Loeb, N.G.; O’Rawe Hinton, P.; Green, R.N. Top-of-atmosphere albedo estimation from angular distribution models: A comparison between two approaches. J. Geophys. Res. Atmos. 1999, 104, 31255–31260. [Google Scholar] [CrossRef]
- For consistency with an aerosol-optical-depth mask applied in the following, as there is no retrieval at larger zenith angles.
- The sunglint angle is defined via: cos(sunglintangle)=sin(θ⊙)sin(θvz)cos(ϕrel)+cos(θ⊙)cos(θvz).
- Note that the CERES team proposes a method to account for aerosols in the clear-sky ocean ADM; see ref. [6]. However, this correction is not actually applied in the GL-SEV processing.
- The presence of aerosols results in a quite diffuse reflection; very different from the strong specular reflection in the clear-sky ocean case. The use of clear-sky ocean ADMs that do not take aerosols into account is therefore particularly problematic.
- De Paepe, B.; Ignatov, A.; Dewitte, S.; Ipe, A. Aerosol retrieval over ocean from SEVIRI for the use in GERB Earth’s radiation budget analyses. Remote Sens. Environ. 2008, 112, 2455–2468. [Google Scholar] [CrossRef]
- Zhang, J.; Christopher, S.A.; Remer, L.A.; Kaufman, Y.J. Shortwave aerosol radiative forcing over cloud-free oceans from Terra: 1. Angular models for aerosols. J. Geophys. Res. Atmos. 2005, 110, D10S23. [Google Scholar] [CrossRef] [Green Version]
- Bertrand, C.; Futyan, J.; Ipe, A.; Gonzalez, L.; Clerbaux, N. Diurnal Asymmetry in the GERB SW Fluxes. IEEE Trans. Geosci. Remote Sens. 2006, 44, 3585–3600. [Google Scholar] [CrossRef]
- Loeb, N.G.; Doelling, D.R.; Wang, H.; Su, W.; Nguyen, C.; Corbett, J.G.; Liang, L.; Mitrescu, C.; Rose, F.G.; Kato, S. Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. J. Clim. 2018, 31, 895–918. [Google Scholar] [CrossRef]
- Minnis, P.; Mayor, S.; Smith, W.L.; Young, D.F. Asymmetry in the diurnal variation of surface albedo. IEEE Trans. Geosci. Remote Sens. 1997, 35, 879–890. [Google Scholar] [CrossRef] [Green Version]
- Dickinson, R.E. Land Surface Processes and Climate-Surface Albedos and Energy Balance. Adv. Geophys. 1983, 25, 305. [Google Scholar] [CrossRef]
- Briegleb, B.P.; Minnis, P.; Ramanathan, V.; Harrison, E. Comparison of Regional Clear-Sky Albedos Inferred from Satellite Observations and Model Computations. J. Clim. Appl. Meteorol. 1986, 25, 214–226. [Google Scholar] [CrossRef]
- Yang, F.; Mitchell, K.; Hou, Y.T.; Dai, Y.; Zeng, X.; Wang, Z.; Liang, X.Z. Dependence of Land Surface Albedo on Solar Zenith Angle: Observations and Model Parameterization. J. Appl. Meteorol. Climatol. 2008, 47, 2963. [Google Scholar] [CrossRef] [Green Version]
- While the branches themselves cannot be physical, one can notice the presence of overimposed instantaneous patterns. In contrast to the branches, those are actually consistent between the two satellites at corresponding times and likely of physical origin. They are in fact already present in SEVIRI narrowband radiances.
- Although an effect due to residual narrowband-to-broadband errors in GL-SEV cannot be excluded, this would not be sufficient to explain the diurnal-asymmetry artefact, which also appears in pure broadband GERB data.
- Further note that any actual observer-independent physical effect with a significant impact on the albedo should remain clearly visible even with swapped branches from MSG-3 to MSG-1. If there were dew [34] in the early morning for instance, the shape of the two morning branches would then be similarly skewed upwards and the apparent symmetry seen here when swapping the morning and afternoon branches would be lost.
- The NLopt Free and Open Source Nonlinear-Optimization Library. Available online: http://github.com/stevengj/nlopt (accessed on 22 April 2021).
- Powell, M.J.D. The NEWUOA software for unconstrained optimization without derivatives. Technical report, DAMTP 2004/NA08, Department of Applied Mathematics and Theoretical Physics, University of Cambridge, 2004. In Proceedings of the 40th Workshop on Large Scale Nonlinear Optimization, Erice, Italy, 22 June–1 July 2004. [Google Scholar]
- Kraft, D. Algorithm 733: TOMP-Fortran modules for optimal control calculations. ACM Trans. Math. Soft 1994, 20, 262–281. [Google Scholar] [CrossRef]
- One could also further include a minimum requested range in cos(θ⊙), especially for high latitudes in winter.
- Dewitte, S.; Clerbaux, N.; Ipe, A.; Baudrez, E.; Moreels, J. Dual view Geostationary Earth Radiation Budget from the Meteosat Second Generation satellites. In EGU General Assembly Conference Abstracts; EGU: Munich, Germany, 2017; p. 6607. [Google Scholar]
- A few aerosol-loaded pixels remain west of Africa in the dual-view region, even in Figure 9d. Correctly masked when seen from MSG-3, they were not identified from MSG-1 (being close to the viewing-zenith limit), and thus reintroduced.
- For each pixel, we define the branches themselves with respect to the local noon, determined as the UTC timeslot with the largest mean cos(θ⊙) value (akin to ref. [32]); the local midnight is calculated as local noon plus 12 h, modulo 24 h.
- Due to the tip, we can expect higher branches to be slightly steeper, and lower branches, flatter. While this can artificially increase the difference between branches for each pixel, it will not affect the qualitative result (i.e., which is higher or lower).
- The large afternoon effect in South America is similarly due to a cloud-detection issue. Note that trying to address it with masks and cuts ultimately creates an imbalance between the branches (artificially giving more weight to one of them). This issue should preferably be dealt with within the GL-SEV data processing itself.
- As a corollary, this of course also means that, together with ref. [37], we do not find that the morning albedo is systematically larger than the afternoon one when such a diurnal asymmetry is present—i.e., what one might have expected if an actual phenomenon such as dew was at play [34].
naively | 0.055 | 0.052 | 0.012 |
with all the masks | 0.014 | 0.013 | 0.004 |
with all the masks + empirical fits | 0.008 | 0.004 | 0.005 |
Masks Only | Masks + Empirical Fits | ||||||
---|---|---|---|---|---|---|---|
Month | Month | ||||||
2017/01 | 0.016 | 0.013 | 0.005 | 2017/01 | 0.011 | 0.006 | 0.006 |
2017/02 | 0.019 | 0.017 | 0.005 | 2017/02 | 0.011 | 0.005 | 0.005 |
2017/03 | 0.017 | 0.015 | 0.004 | 2017/03 | 0.010 | 0.006 | 0.004 |
2017/04 | 0.016 | 0.015 | 0.004 | 2017/04 | 0.009 | 0.006 | 0.004 |
2017/05 | 0.015 | 0.014 | 0.003 | 2017/05 | 0.009 | 0.006 | 0.004 |
2017/06 | 0.016 | 0.015 | 0.004 | 2017/06 | 0.009 | 0.006 | 0.005 |
2017/07 | 0.018 | 0.016 | 0.005 | 2017/07 | 0.009 | 0.005 | 0.005 |
2017/08 | 0.021 | 0.018 | 0.006 | 2017/08 | 0.011 | 0.006 | 0.006 |
2017/09 | 0.020 | 0.018 | 0.005 | 2017/09 | 0.011 | 0.006 | 0.006 |
2017/10 | 0.017 | 0.016 | 0.004 | 2017/10 | 0.009 | 0.005 | 0.005 |
2017/11 | 0.014 | 0.013 | 0.004 | 2017/11 | 0.009 | 0.005 | 0.004 |
2017/12 | 0.015 | 0.013 | 0.005 | 2017/12 | 0.010 | 0.005 | 0.005 |
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Payez, A.; Dewitte, S.; Clerbaux, N. Dual View on Clear-Sky Top-of-Atmosphere Albedos from Meteosat Second Generation Satellites. Remote Sens. 2021, 13, 1655. https://doi.org/10.3390/rs13091655
Payez A, Dewitte S, Clerbaux N. Dual View on Clear-Sky Top-of-Atmosphere Albedos from Meteosat Second Generation Satellites. Remote Sensing. 2021; 13(9):1655. https://doi.org/10.3390/rs13091655
Chicago/Turabian StylePayez, Alexandre, Steven Dewitte, and Nicolas Clerbaux. 2021. "Dual View on Clear-Sky Top-of-Atmosphere Albedos from Meteosat Second Generation Satellites" Remote Sensing 13, no. 9: 1655. https://doi.org/10.3390/rs13091655